Mobile devices having an application for providing a weather forecast are currently known and used. However, the weather forecast is based on temporally stale information. Specifically, the forecast is based upon a model that is typically run every 6 hours. Accordingly, the weather forecast information is based upon models that are not reflective of current atmospheric conditions.
Further, the weather forecast is based on global-scale models featuring coarse horizontal resolutions. For instance, current models used by forecasting entities may use a horizontal grid resolution of approximately 50-100 km for a forecast covering an area of 1000 km. Thus, current weather forecasts do not capture the influences of the local underlying topography and land use. Using global-scale models alone may suffice in non-dynamic weather conditions, but will typically be inadequate if weather conditions are changing rapidly or if the local area features significant terrain and/or dramatic land-use transitions.
Accordingly, it remains desirable to have a method or system configured to generate a weather forecast optimized for a local geographic zone by using a high-resolution (both horizontally and vertically) physics-based weather model with the best possible 3-d picture of the atmosphere for model initialization and by using built-in high resolution land use and topography datasets.